A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization

Nooraziah Ahmad, and Tiagrajah V. Janahiraman, A comparison on optimization of surface roughness in machining AISI 1045 steel using Taguchi method, genetic algorithm and particle swarm optimization. In: 2015 IEEE Conference on Systems, Process and Control (ICSPC). IIEEE Malaysia Section Control Systems Chapter, pp. 129-133. ISBN 9781467376549

Official URL: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnum...

Abstract

AISI 1045 steel is one of the most widely used steel in the manufacturing industry. In order to have the best quality of turned AISI 1045 steel product, surface roughness is being considered as output parameter. The two purposes of this research are to model the surface roughness using response surface methodology and to compare the different types of optimization approaches in order to identify the optimum surface roughness with particular combination of cutting parameters in turning operation. The result obtained from this study showed that the values from RSMs' prediction are 99.3% similar to the experimental values. While, particle swarm optimization give the lowest surface roughness when compared to Taguchi method and genetic algorithm and it can optimize faster than genetic algorithm.

Item Type: Book Section
ISBN: 9781467376549
Keywords: Optimization; AISI 1045 steel; Surface roughness
Faculty: Faculty of Creative Technology and Heritage
Deposited By: En. Pahmi Abdullah
Date Deposited: 14 Aug 2016 01:54
Last Modified: 14 Aug 2016 02:37
URI: http://umkeprints.umk.edu.my/id/eprint/6103

Actions (login required)

View Item View Item